Note

  1. Learn how to design trading strategy from Rob
  1. Refine the instrument level through portfolio level

A) Acknowledgments

All the information contained in this document is drawn from my personal experience, as well as insights gleaned from the books written by Robert Carver.

B) Things to know

Backtesting Advice

  • Keep it simple: more complicate will lead to over-fitting.
  • Fewer alternatives: More variation, more likely to select unprofitable rule by chance. (Multiple Comparisons problem)
  • Use expanding out of sample or rolling (walk forward) with proper period
  • Don’t drop rules casually: since it is unlikely to differentiate rule’s performance.
  • Pull data across instruments.
  • Compare on the same return distributions: positive shewed with positive shewed.
  • Compare return relatively to benchmarks.
  • Use weighted average of rules: Single rule will lead to overconfident, and it is unlikely to prove that which one is better.
  • If correlation of two rules are more than .95 then we can drop one.
  • Drop too slow due to law of active management.
  • Drop too fast since high cost
  • Don’t drop rule purely because performance.

Backtesting Problem

  1. Overfitting

    • Type of fitting: Explicit, Implicit and Tatic.
    • Too much variation (too many degree of freedom) - “multiple comparisons problem”
    • Not enough data (need more than 30 years for rule that highly correlated of 0.8)
    • Too complex system.

  2. Survivorship bias

    • Not consider a delisted stock.

  3. Implementation

    • Cost
    • Liquidity
    • Capital limit

  4. Data correctness

    • Mislead data: single big jump

Backtesting Approach

  1. In sample
  2. Half out of sample
  3. Expanding out of sample (anchored fitting): Recommended!
  4. Rolling out of sample (walk forward)

Checking Robustness

  1. parameter sensitivity
  2. Lag of signal
  3. Additional slippage
  4. All market condition, fake crisis, weakness environment.

Components of System

  1. Universe: tradable markets.
  2. Buy/Sell Engine: buy/sell conditions with parameters.
  3. Position Sizing: how much to buy/sell
  4. Execution: execution methods. 5 Rebalancing period

C) Designing System

1. Instrument Level through Portfolio Level

Single Instrument Level

Understand characteristic of trading rules

  • Get the characteristic of instrument given param, cost, speed, objective and correlation.
  • Parameter selection: Select or drop parameter
  • Compare with naive approach: buy and hold, random entry exit.
  • Use random data

Understand characteristic of position sizing method

  • Compare with naive approach: standardized volatility, fix percentage
  • Apply pyramid approach.

Analyze trading rule along with position sizing method

  • Prove that given trading rule with particular position sizing method outperform naive.
Portfolio Level
  • Apply portfolio level to include diversification benefits by apply it on three level: Avg of single instrument (no diversification), diversify through same asset class, diversify through different asset class.

2. Designing a Trading Strategy.

3. How to choose rules

  1. understand characteristic of small number of variation or rule
  • how it behave in a paricular type of market, speed and correlation
  • Allocate forecast weight to each variation with consideration of uncertainty of sharp ratio (Real data: return)

D) Additional Plot

  1. Boxplot of sharp across differnt pairs.

  2. window length on x with sharp ratio on y [systematic trading - page 59]

  3. check sharp ratio and correlation

  • Look back haft or third of trend length

  • Information is average sharp ratio of fake data.

  1. Check turnover

  • Check turn over